Engineering Data Pipelines

Community

telagod

engineering-data-pipelines

Data engineering knowledge reference covering Airflow, Dagster, Kafka Streams, Flink, dbt, and data quality patterns. Use when building data pipelines, ETL workflows, stream processing, or data quality checks.

Overview

Publisher	telagod
Repository	`code-abyss`
Skill name	`engineering-data-pipelines`
Stars	242
Forks	33
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by telagod on GitHub. Read the source before you install it.

Installation

Install the Engineering Data Pipelines AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/telagod/code-abyss/tree/main/skills/engineering-data-pipelines
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/telagod/code-abyss.git /tmp/code-abyss
mkdir -p .claude/skills
cp -r /tmp/code-abyss/skills/engineering-data-pipelines .claude/skills/engineering-data-pipelines

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Engineering Data Pipelines in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Engineering Data Pipelines on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Engineering Data Pipelines is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

数据工程域 · Data Engineering

判断先于执行：决定「是否做 / 选什么 / 如何取舍」（栈、方案、架构、权衡）前，先读领域判断内核 skills/_kernel/backend/SKILL.md——它管 judgment，本秘典管 execution；冲突时以内核判断为准。


编排：Airflow(调度) | Dagster(资产) | Prefect(现代流)
流处理：Kafka Streams(嵌入式) | Flink(集群) | Spark Streaming
质量：Great Expectations | dbt tests | Soda Core

编排检查项

幂等(UPSERT/分区覆盖) | 增量(WHERE updated_at > last_run) | 事件驱动触发 | 跨 DAG 依赖 | 数据血缘(ref()/Asset deps)

流处理检查项

质量检查项

分层验证(源→转换→目标) | 完整性+准确性+一致性 | 及时性阈值 | 加权评分 | 告警(Slack/PagerDuty)

工具对比、API 用法、质量维度详见 references/details.md

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

references/details.md2 KB

Frequently asked questions

What does the Engineering Data Pipelines AI skill do?

Why use Engineering Data Pipelines on TypingMind?

Because you install it once and use it with any model. Engineering Data Pipelines is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Engineering Data Pipelines in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/telagod/code-abyss/tree/main/skills/engineering-data-pipelines. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Engineering Data Pipelines?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Engineering Data Pipelines?

As many as you like. As long as a model supports skills, you can use Engineering Data Pipelines with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Engineering Data Pipelines AI skill free?

Yes. It is published on GitHub by telagod under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

数据工程域 · Data Engineering

编排检查项

流处理检查项

质量检查项

Bundled files

Frequently asked questions

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